ggoh29 / Simplicial-neural-network-benchmark
Simplicial neural network benchmarking software
☆17Updated 2 years ago
Alternatives and similar repositories for Simplicial-neural-network-benchmark:
Users that are interested in Simplicial-neural-network-benchmark are comparing it to the libraries listed below
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆14Updated last year
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆75Updated last year
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated last year
- Topological Graph Neural Networks (ICLR 2022)☆120Updated 2 years ago
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆55Updated 2 years ago
- Graph Positional and Structural Encoder☆46Updated 3 weeks ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))☆17Updated 7 months ago
- [ECCV'22] Equivariant Hypergraph Neural Networks, in PyTorch☆29Updated last year
- ☆27Updated last month
- Official repository for the ICLR 2022 paper "Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions"…☆14Updated 2 years ago
- Gradient gating (ICLR 2023)☆53Updated last year
- Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, an…☆16Updated last year
- Official Code Repository for the paper "Graph Ordering Attention Networks"☆21Updated last year
- ☆52Updated 2 years ago
- ☆30Updated last year
- CAT-Walk is an inducive method that learns hyperedge representations via a novel higher-order random walk, SetWalk.☆13Updated last year
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆43Updated 10 months ago
- Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…☆76Updated 3 years ago
- A library for subgraph GNN based on pyg☆41Updated 2 months ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆32Updated 4 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆78Updated 3 years ago
- Scattering GCN: overcoming oversmoothness in graph convolutional networks☆25Updated 2 years ago
- ☆17Updated last year
- Code for our paper "Attending to Graph Transformers"☆85Updated last year
- DiffWire: Inductive Graph Rewiring via the Lovász Bound. In Proceedings of the First Learning on Graphs Conference. 2022. Adrian Arnaiz-R…☆18Updated 2 years ago
- DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data, IEEE BigData 2022☆27Updated 2 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆86Updated last year
- A Note On Over-Smoothing for Graph Neural Network☆19Updated 4 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆43Updated 2 years ago